Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control,Diabetologia

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Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control
Diabetologia ( IF 8.2 ) Pub Date : 2021-07-06 , DOI: 10.1007/s00125-021-05491-7
Johanne Tremblay ₁ , Mounsif Haloui ₁ , Redha Attaoua ₁ , Ramzan Tahir ₁ , Camil Hishmih ₁ , François Harvey ₁ , François-Christophe Marois-Blanchet ₁ , Carole Long ₁ , Paul Simon ₁ , Lara Santucci ₁ , Candan Hizel ₁ , John Chalmers ₂ , Michel Marre ₃ , Stephen Harrap ₄ , Renata Cífková ₅ , Alena Krajčoviechová ₅ , David R Matthews ₆ , Bryan Williams ₇ , Neil Poulter ₈ , Sophia Zoungas ₉ , Stephen Colagiuri ₁₀ , Giuseppe Mancia ₁₁ , Diederick E Grobbee ₁₂ , Anthony Rodgers ₂ , Liusheng Liu ₁₃ , Mawussé Agbessi ₁₄ , Vanessa Bruat ₁₄ , Marie-Julie Favé ₁₄ , Michelle P Harwood ₁₄ , Philip Awadalla _{14,

15} , Mark Woodward _{2,

8,

16} , Julie G Hussin _{17,

18} , Pavel Hamet ₁

Affiliation

Department of Medicine, University of Montréal, CRCHUM, Québec, Canada.
The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia.
Clinique Ambroise Paré, Neuilly-sur-Seine, and Centre de Recherches des Cordeliers, Paris, France.
Department of Physiology, University of Melbourne, Melbourne, VIC, Australia.
Center for Cardiovascular Prevention, First Faculty of Medicine, Charles University in Prague and Thomayer Hospital, Prague, Czech Republic.
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.
University College London, Institute of Cardiovascular Science, London, UK.
School of Public Health, Faculty of Medicine, Imperial College London, London, UK.
School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Boden Institute, University of Sydney, Sydney, NSW, Australia.
Istituto Auxologico Italiano, University of Milano, Bicocca, Italy.
Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands.
Beijing Hypertension League Institute, Beijing, China.
Ontario Institute for Cancer Research, Toronto, ON, Canada.
Department of Molecular Genetics and Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
The George Institute for Global Health, School of Public Health, Imperial College London, London, UK.
Montreal Heart Institute, Research Center, Montréal, Québec, Canada.
Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada.

Aims/hypothesis

Type 2 diabetes increases the risk of cardiovascular and renal complications, but early risk prediction could lead to timely intervention and better outcomes. Genetic information can be used to enable early detection of risk.

Methods

We developed a multi-polygenic risk score (multiPRS) that combines ten weighted PRSs (10 wPRS) composed of 598 SNPs associated with main risk factors and outcomes of type 2 diabetes, derived from summary statistics data of genome-wide association studies. The 10 wPRS, first principal component of ethnicity, sex, age at onset and diabetes duration were included into one logistic regression model to predict micro- and macrovascular outcomes in 4098 participants in the ADVANCE study and 17,604 individuals with type 2 diabetes in the UK Biobank study.

Results

The model showed a similar predictive performance for cardiovascular and renal complications in different cohorts. It identified the top 30% of ADVANCE participants with a mean of 3.1-fold increased risk of major micro- and macrovascular events (p = 6.3 × 10⁻²¹ and p = 9.6 × 10⁻³¹, respectively) and a 4.4-fold (p = 6.8 × 10⁻³³) higher risk of cardiovascular death. While in ADVANCE overall, combined intensive blood pressure and glucose control decreased cardiovascular death by 24%, the model identified a high-risk group in whom it decreased the mortality rate by 47%, and a low-risk group in whom it had no discernible effect. High-risk individuals had the greatest absolute risk reduction with a number needed to treat of 12 to prevent one cardiovascular death over 5 years.

Conclusions/interpretation

This novel multiPRS model stratified individuals with type 2 diabetes according to risk of complications and helped to target earlier those who would receive greater benefit from intensive therapy.

Graphical abstract

中文翻译：

多基因风险评分可预测糖尿病并发症及其对强化血压和血糖控制的反应

目标/假设

2 型糖尿病会增加心血管和肾脏并发症的风险，但早期风险预测可能会导致及时干预和更好的结果。遗传信息可用于早期发现风险。

方法

我们开发了一个多基因风险评分 (multiPRS)，它结合了 10 个加权 PRS (10 wPRS)，由 598 个与 2 型糖尿病的主要风险因素和结果相关的 SNP 组成，来自全基因组关联研究的汇总统计数据。将 10 个 wPRS（种族、性别、发病年龄和糖尿病持续时间的第一个主要成分）纳入一个逻辑回归模型，以预测 ADVANCE 研究中 4098 名参与者和英国生物库中 17,604 名 2 型糖尿病患者的微血管和大血管结果学习。

结果

该模型在不同队列中显示出对心血管和肾脏并发症的相似预测性能。它确定了前 30% 的 ADVANCE 参与者，其主要微血管和大血管事件的风险平均增加了 3.1 倍（分别为p = 6.3 × 10 ^-21和p = 9.6 × 10 ^-31）和 4.4 倍（p = 6.8 × 10 ^-33) 心血管死亡的风险更高。虽然总体而言，在 ADVANCE 中，联合强化血压和血糖控制将心血管死亡降低了 24%，但该模型确定了一个高风险组，其死亡率降低了 47%，而一个低风险组则无法识别影响。高风险个体的绝对风险降低幅度最大，需要治疗 12 人才能在 5 年内预防 1 例心血管死亡。